{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Behold the Mighty Pileup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:27:20.179659Z",
     "start_time": "2018-05-08T02:27:20.165603Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib.gridspec import GridSpec\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "mpl.style.use('seaborn-white')\n",
    "import multiprocess as mp\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import bioframe\n",
    "import cooltools\n",
    "import cooler\n",
    "import bbi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:27:12.489464Z",
     "start_time": "2018-05-08T02:27:12.129215Z"
    }
   },
   "outputs": [],
   "source": [
    "mm9 = bioframe.fetch_chromsizes('mm9')\n",
    "chromsizes = bioframe.fetch_chromsizes('mm9')\n",
    "chromosomes = list(chromsizes.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:28:21.018661Z",
     "start_time": "2018-05-08T02:28:21.000317Z"
    }
   },
   "outputs": [],
   "source": [
    "conditions = ['WT', 'dN']\n",
    "binsize = 10000\n",
    "\n",
    "cooler_paths = {    \n",
    "    'WT' : f'data/UNTR.{binsize}.cool',\n",
    "    'T'  : f'data/TAM.{binsize}.cool',\n",
    "    'dN' : f'data/NIPBL.{binsize}.cool',\n",
    "}\n",
    "long_names = {\n",
    "    'WT': 'Wildtype',\n",
    "    'T' : 'TAM',\n",
    "    'dN': 'NipblKO',\n",
    "}\n",
    "pal = sns.color_palette('colorblind')\n",
    "colors = {\n",
    "    'WT': pal[0],\n",
    "    'T' : '#333333',\n",
    "    'dN': pal[2],\n",
    "}\n",
    "\n",
    "clrs = {\n",
    "    cond: cooler.Cooler(cooler_paths[cond]) for cond in conditions\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single landmark pileup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:28:21.345151Z",
     "start_time": "2018-05-08T02:28:21.342586Z"
    }
   },
   "outputs": [],
   "source": [
    "from cooltools import snipping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:28:21.668278Z",
     "start_time": "2018-05-08T02:28:21.521844Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>fc</th>\n",
       "      <th>-log10p</th>\n",
       "      <th>-log10q</th>\n",
       "      <th>relSummit</th>\n",
       "      <th>chrom_m</th>\n",
       "      <th>start_m</th>\n",
       "      <th>end_m</th>\n",
       "      <th>name_m</th>\n",
       "      <th>score_m</th>\n",
       "      <th>strand_m</th>\n",
       "      <th>pval_m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr14</td>\n",
       "      <td>73909345</td>\n",
       "      <td>73910139</td>\n",
       "      <td>Peak_1</td>\n",
       "      <td>2864</td>\n",
       "      <td>.</td>\n",
       "      <td>66.97627</td>\n",
       "      <td>286.44055</td>\n",
       "      <td>277.00751</td>\n",
       "      <td>386</td>\n",
       "      <td>chr14</td>\n",
       "      <td>73909703</td>\n",
       "      <td>73909716</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>12.8061</td>\n",
       "      <td>-</td>\n",
       "      <td>1.610000e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr8</td>\n",
       "      <td>73292691</td>\n",
       "      <td>73293764</td>\n",
       "      <td>Peak_10</td>\n",
       "      <td>2288</td>\n",
       "      <td>.</td>\n",
       "      <td>59.05101</td>\n",
       "      <td>228.89639</td>\n",
       "      <td>222.17598</td>\n",
       "      <td>738</td>\n",
       "      <td>chr8</td>\n",
       "      <td>73293454</td>\n",
       "      <td>73293467</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>14.2242</td>\n",
       "      <td>+</td>\n",
       "      <td>6.080000e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr10</td>\n",
       "      <td>99078331</td>\n",
       "      <td>99079198</td>\n",
       "      <td>Peak_100</td>\n",
       "      <td>1567</td>\n",
       "      <td>.</td>\n",
       "      <td>40.02444</td>\n",
       "      <td>156.79012</td>\n",
       "      <td>151.30066</td>\n",
       "      <td>303</td>\n",
       "      <td>chr10</td>\n",
       "      <td>99078650</td>\n",
       "      <td>99078663</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>19.7758</td>\n",
       "      <td>+</td>\n",
       "      <td>6.020000e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr19</td>\n",
       "      <td>44437901</td>\n",
       "      <td>44438397</td>\n",
       "      <td>Peak_1000</td>\n",
       "      <td>741</td>\n",
       "      <td>.</td>\n",
       "      <td>20.84388</td>\n",
       "      <td>74.12866</td>\n",
       "      <td>69.69677</td>\n",
       "      <td>273</td>\n",
       "      <td>chr19</td>\n",
       "      <td>44438190</td>\n",
       "      <td>44438203</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>15.1212</td>\n",
       "      <td>-</td>\n",
       "      <td>3.280000e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr1</td>\n",
       "      <td>145853760</td>\n",
       "      <td>145854152</td>\n",
       "      <td>Peak_10000</td>\n",
       "      <td>355</td>\n",
       "      <td>.</td>\n",
       "      <td>12.38549</td>\n",
       "      <td>35.59266</td>\n",
       "      <td>32.22501</td>\n",
       "      <td>189</td>\n",
       "      <td>chr1</td>\n",
       "      <td>145853924</td>\n",
       "      <td>145853937</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>17.6242</td>\n",
       "      <td>+</td>\n",
       "      <td>3.710000e-07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   chrom      start        end        name  score strand        fc    -log10p  \\\n",
       "0  chr14   73909345   73910139      Peak_1   2864      .  66.97627  286.44055   \n",
       "1   chr8   73292691   73293764     Peak_10   2288      .  59.05101  228.89639   \n",
       "2  chr10   99078331   99079198    Peak_100   1567      .  40.02444  156.79012   \n",
       "3  chr19   44437901   44438397   Peak_1000    741      .  20.84388   74.12866   \n",
       "4   chr1  145853760  145854152  Peak_10000    355      .  12.38549   35.59266   \n",
       "\n",
       "     -log10q  relSummit chrom_m    start_m      end_m      name_m  score_m  \\\n",
       "0  277.00751        386   chr14   73909703   73909716  CTCF_mouse  12.8061   \n",
       "1  222.17598        738    chr8   73293454   73293467  CTCF_mouse  14.2242   \n",
       "2  151.30066        303   chr10   99078650   99078663  CTCF_mouse  19.7758   \n",
       "3   69.69677        273   chr19   44438190   44438203  CTCF_mouse  15.1212   \n",
       "4   32.22501        189    chr1  145853924  145853937  CTCF_mouse  17.6242   \n",
       "\n",
       "  strand_m        pval_m  \n",
       "0        -  1.610000e-05  \n",
       "1        +  6.080000e-06  \n",
       "2        +  6.020000e-08  \n",
       "3        -  3.280000e-06  \n",
       "4        +  3.710000e-07  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctcf = pd.read_table('data/CtcfCtrl.mm9__VS__InputCtrl.mm9.narrowPeak_with_motif.txt.gz')\n",
    "ctcf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:28:21.774414Z",
     "start_time": "2018-05-08T02:28:21.731154Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>strand</th>\n",
       "      <th>fc</th>\n",
       "      <th>-log10p</th>\n",
       "      <th>-log10q</th>\n",
       "      <th>relSummit</th>\n",
       "      <th>chrom_m</th>\n",
       "      <th>start_m</th>\n",
       "      <th>end_m</th>\n",
       "      <th>name_m</th>\n",
       "      <th>score_m</th>\n",
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       "      <th>pval_m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39612</th>\n",
       "      <td>chr2</td>\n",
       "      <td>28440591</td>\n",
       "      <td>28441124</td>\n",
       "      <td>Peak_7</td>\n",
       "      <td>2444</td>\n",
       "      <td>.</td>\n",
       "      <td>67.20400</td>\n",
       "      <td>244.48576</td>\n",
       "      <td>237.52400</td>\n",
       "      <td>289</td>\n",
       "      <td>chr2</td>\n",
       "      <td>28440889</td>\n",
       "      <td>28440902</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>17.1879</td>\n",
       "      <td>+</td>\n",
       "      <td>5.530000e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr14</td>\n",
       "      <td>73909345</td>\n",
       "      <td>73910139</td>\n",
       "      <td>Peak_1</td>\n",
       "      <td>2864</td>\n",
       "      <td>.</td>\n",
       "      <td>66.97627</td>\n",
       "      <td>286.44055</td>\n",
       "      <td>277.00751</td>\n",
       "      <td>386</td>\n",
       "      <td>chr14</td>\n",
       "      <td>73909703</td>\n",
       "      <td>73909716</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>12.8061</td>\n",
       "      <td>-</td>\n",
       "      <td>1.610000e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8403</th>\n",
       "      <td>chr12</td>\n",
       "      <td>85930537</td>\n",
       "      <td>85931240</td>\n",
       "      <td>Peak_18</td>\n",
       "      <td>2221</td>\n",
       "      <td>.</td>\n",
       "      <td>66.84265</td>\n",
       "      <td>222.16884</td>\n",
       "      <td>215.60326</td>\n",
       "      <td>320</td>\n",
       "      <td>chr12</td>\n",
       "      <td>85930837</td>\n",
       "      <td>85930850</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>17.9212</td>\n",
       "      <td>+</td>\n",
       "      <td>2.800000e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5278</th>\n",
       "      <td>chr11</td>\n",
       "      <td>78267090</td>\n",
       "      <td>78267719</td>\n",
       "      <td>Peak_15</td>\n",
       "      <td>2240</td>\n",
       "      <td>.</td>\n",
       "      <td>66.48611</td>\n",
       "      <td>224.05933</td>\n",
       "      <td>217.43312</td>\n",
       "      <td>301</td>\n",
       "      <td>chr11</td>\n",
       "      <td>78267350</td>\n",
       "      <td>78267363</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>17.9636</td>\n",
       "      <td>-</td>\n",
       "      <td>2.770000e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40800</th>\n",
       "      <td>chr11</td>\n",
       "      <td>98203663</td>\n",
       "      <td>98204470</td>\n",
       "      <td>Peak_8</td>\n",
       "      <td>2370</td>\n",
       "      <td>.</td>\n",
       "      <td>65.88831</td>\n",
       "      <td>237.03339</td>\n",
       "      <td>230.20671</td>\n",
       "      <td>426</td>\n",
       "      <td>chr11</td>\n",
       "      <td>98204100</td>\n",
       "      <td>98204113</td>\n",
       "      <td>CTCF_mouse</td>\n",
       "      <td>20.5697</td>\n",
       "      <td>-</td>\n",
       "      <td>2.070000e-08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end     name  score strand        fc    -log10p  \\\n",
       "39612   chr2  28440591  28441124   Peak_7   2444      .  67.20400  244.48576   \n",
       "0      chr14  73909345  73910139   Peak_1   2864      .  66.97627  286.44055   \n",
       "8403   chr12  85930537  85931240  Peak_18   2221      .  66.84265  222.16884   \n",
       "5278   chr11  78267090  78267719  Peak_15   2240      .  66.48611  224.05933   \n",
       "40800  chr11  98203663  98204470   Peak_8   2370      .  65.88831  237.03339   \n",
       "\n",
       "         -log10q  relSummit chrom_m   start_m     end_m      name_m  score_m  \\\n",
       "39612  237.52400        289    chr2  28440889  28440902  CTCF_mouse  17.1879   \n",
       "0      277.00751        386   chr14  73909703  73909716  CTCF_mouse  12.8061   \n",
       "8403   215.60326        320   chr12  85930837  85930850  CTCF_mouse  17.9212   \n",
       "5278   217.43312        301   chr11  78267350  78267363  CTCF_mouse  17.9636   \n",
       "40800  230.20671        426   chr11  98204100  98204113  CTCF_mouse  20.5697   \n",
       "\n",
       "      strand_m        pval_m  \n",
       "39612        +  5.530000e-07  \n",
       "0            -  1.610000e-05  \n",
       "8403         +  2.800000e-07  \n",
       "5278         -  2.770000e-07  \n",
       "40800        -  2.070000e-08  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sites = ctcf.sort_values('fc', ascending=False).iloc[:1000]\n",
    "sites.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:28:22.060162Z",
     "start_time": "2018-05-08T02:28:21.935484Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 windows, after assigning supports\n"
     ]
    },
    {
     "data": {
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       "      <th>39612</th>\n",
       "      <td>chr2</td>\n",
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       "      <td>2784</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr14</td>\n",
       "      <td>73300000</td>\n",
       "      <td>74510000</td>\n",
       "      <td>7330</td>\n",
       "      <td>7451</td>\n",
       "      <td>-</td>\n",
       "      <td>chr14:0-125194864</td>\n",
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       "    <tr>\n",
       "      <th>8403</th>\n",
       "      <td>chr12</td>\n",
       "      <td>85330000</td>\n",
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       "      <td>8533</td>\n",
       "      <td>8654</td>\n",
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       "      <td>chr12:0-121257530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5278</th>\n",
       "      <td>chr11</td>\n",
       "      <td>77660000</td>\n",
       "      <td>78870000</td>\n",
       "      <td>7766</td>\n",
       "      <td>7887</td>\n",
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       "      <td>chr11:0-121843856</td>\n",
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       "    <tr>\n",
       "      <th>40800</th>\n",
       "      <td>chr11</td>\n",
       "      <td>97600000</td>\n",
       "      <td>98810000</td>\n",
       "      <td>9760</td>\n",
       "      <td>9881</td>\n",
       "      <td>-</td>\n",
       "      <td>chr11:0-121843856</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       chrom     start       end    lo    hi strand             region\n",
       "39612   chr2  27840000  29050000  2784  2905      +   chr2:0-181748087\n",
       "0      chr14  73300000  74510000  7330  7451      -  chr14:0-125194864\n",
       "8403   chr12  85330000  86540000  8533  8654      +  chr12:0-121257530\n",
       "5278   chr11  77660000  78870000  7766  7887      -  chr11:0-121843856\n",
       "40800  chr11  97600000  98810000  9760  9881      -  chr11:0-121843856"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "supports = [(chrom, 0, chromsizes[chrom]) for chrom in chromosomes]\n",
    "\n",
    "flank = 600000\n",
    "windows = snipping.make_bin_aligned_windows(\n",
    "    binsize, \n",
    "    sites['chrom'], \n",
    "    (sites['start_m'] + sites['end_m'])//2,\n",
    "    flank_bp=flank)\n",
    "windows['strand'] = sites['strand_m']\n",
    "windows = snipping.assign_regions(windows, supports)\n",
    "windows = windows.dropna()\n",
    "\n",
    "print(len(windows), 'windows, after assigning supports')\n",
    "windows.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:29:14.972258Z",
     "start_time": "2018-05-08T02:28:22.229994Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nezar/miniconda3/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:14: RuntimeWarning: Mean of empty slice\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "stacks = {}\n",
    "piles = {}\n",
    "for cond in conditions:\n",
    "    expected = pd.read_table(f'data/{long_names[cond]}.{binsize//1000}kb.expected.cis.tsv')\n",
    "    snipper = snipping.ObsExpSnipper(clrs[cond], expected)\n",
    "    \n",
    "    stack = snipping.pileup(windows, snipper.select, snipper.snip)\n",
    "    \n",
    "    # mirror reflect snippets whose feature is on the opposite strand\n",
    "    mask = np.array(windows.strand == '+', dtype=bool)\n",
    "    stack[:, :, mask] = stack[::-1, ::-1, mask]\n",
    "    \n",
    "    stacks[cond] = stack\n",
    "    piles[cond] = np.nanmean(stack, axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:29:15.391667Z",
     "start_time": "2018-05-08T02:29:14.974518Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7fa2ad90a128>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa2ad9d6128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gs = GridSpec(nrows=1, ncols=len(conditions) + 1, width_ratios=[20] * len(conditions) + [1])\n",
    "plt.figure(figsize=(5 * len(conditions), 5))\n",
    "\n",
    "opts = dict(\n",
    "    vmin=-0.75,\n",
    "    vmax=0.75,\n",
    "    extent=[-flank//1000, flank//1000, -flank//1000, flank//1000],\n",
    "    cmap='coolwarm'\n",
    ")\n",
    "\n",
    "for i, cond in enumerate(conditions):\n",
    "    ax = plt.subplot(gs[i])\n",
    "    img = ax.matshow(\n",
    "        np.log2(piles[cond]),  \n",
    "        **opts)\n",
    "    ax.xaxis.tick_bottom()\n",
    "    if i > 0:\n",
    "        ax.yaxis.set_visible(False)\n",
    "    plt.title(long_names[cond])\n",
    "\n",
    "ax = plt.subplot(gs[len(conditions)])\n",
    "plt.colorbar(img, cax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspect examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:33:53.987652Z",
     "start_time": "2018-05-08T02:33:53.664573Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "74fd142dd482403b8e47109913bda5c1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>interactive</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "interactive(children=(IntSlider(value=499, description='i', max=999), Output()), _dom_classes=('widget-interact',))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipywidgets import interact\n",
    "\n",
    "gs = GridSpec(nrows=1, ncols=len(conditions) + 1, width_ratios=[20] * len(conditions) + [1])\n",
    "n_examples = len(windows)\n",
    "\n",
    "@interact(i=(0, n_examples-1))\n",
    "def f(i):\n",
    "    plt.figure(figsize=(5 * len(conditions), 5))\n",
    "    for j, cond in enumerate(conditions):\n",
    "        ax = plt.subplot(gs[j])\n",
    "        img = ax.matshow(\n",
    "            np.log2(stacks[cond][:, :, i]),  \n",
    "            **opts)\n",
    "        ax.xaxis.tick_bottom()\n",
    "        if i > 0:\n",
    "            ax.yaxis.set_visible(False)\n",
    "        plt.title(long_names[cond])\n",
    "        plt.axvline(0, c='g', ls='--')\n",
    "        plt.axhline(0, c='g', ls='--')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Piling up paired landmarks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:47:51.763683Z",
     "start_time": "2018-05-08T02:47:51.741619Z"
    }
   },
   "outputs": [],
   "source": [
    "anchor_dist = 300000\n",
    "anchor_flank = 10000\n",
    "sites = pd.read_table('data/ctcf-sites.paired.300kb_flank10kb.tsv.1')\n",
    "\n",
    "# \"convergent\" orientation of paired CTCF motifs\n",
    "sites = sites[(sites['strand1'] == '+') & (sites['strand2'] == '-')]\n",
    "\n",
    "print(len(sites))\n",
    "sites.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:49:19.565496Z",
     "start_time": "2018-05-08T02:49:19.325373Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chrom1</th>\n",
       "      <th>start1</th>\n",
       "      <th>end1</th>\n",
       "      <th>lo1</th>\n",
       "      <th>hi1</th>\n",
       "      <th>strand1</th>\n",
       "      <th>chrom2</th>\n",
       "      <th>start2</th>\n",
       "      <th>end2</th>\n",
       "      <th>lo2</th>\n",
       "      <th>hi2</th>\n",
       "      <th>strand2</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chr11</td>\n",
       "      <td>97950000</td>\n",
       "      <td>98460000</td>\n",
       "      <td>9795</td>\n",
       "      <td>9846</td>\n",
       "      <td>+</td>\n",
       "      <td>chr11</td>\n",
       "      <td>98360000</td>\n",
       "      <td>98870000</td>\n",
       "      <td>9836</td>\n",
       "      <td>9887</td>\n",
       "      <td>-</td>\n",
       "      <td>chr11:0-121843856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>chr2</td>\n",
       "      <td>27800000</td>\n",
       "      <td>28310000</td>\n",
       "      <td>2780</td>\n",
       "      <td>2831</td>\n",
       "      <td>+</td>\n",
       "      <td>chr2</td>\n",
       "      <td>28190000</td>\n",
       "      <td>28700000</td>\n",
       "      <td>2819</td>\n",
       "      <td>2870</td>\n",
       "      <td>-</td>\n",
       "      <td>chr2:0-181748087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>chr8</td>\n",
       "      <td>72650000</td>\n",
       "      <td>73160000</td>\n",
       "      <td>7265</td>\n",
       "      <td>7316</td>\n",
       "      <td>+</td>\n",
       "      <td>chr8</td>\n",
       "      <td>73040000</td>\n",
       "      <td>73550000</td>\n",
       "      <td>7304</td>\n",
       "      <td>7355</td>\n",
       "      <td>-</td>\n",
       "      <td>chr8:0-131738871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>chr7</td>\n",
       "      <td>74120000</td>\n",
       "      <td>74630000</td>\n",
       "      <td>7412</td>\n",
       "      <td>7463</td>\n",
       "      <td>+</td>\n",
       "      <td>chr7</td>\n",
       "      <td>74520000</td>\n",
       "      <td>75030000</td>\n",
       "      <td>7452</td>\n",
       "      <td>7503</td>\n",
       "      <td>-</td>\n",
       "      <td>chr7:0-152524553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>chr9</td>\n",
       "      <td>77190000</td>\n",
       "      <td>77700000</td>\n",
       "      <td>7719</td>\n",
       "      <td>7770</td>\n",
       "      <td>+</td>\n",
       "      <td>chr9</td>\n",
       "      <td>77600000</td>\n",
       "      <td>78110000</td>\n",
       "      <td>7760</td>\n",
       "      <td>7811</td>\n",
       "      <td>-</td>\n",
       "      <td>chr9:0-124076172</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  chrom1    start1      end1   lo1   hi1 strand1 chrom2    start2      end2  \\\n",
       "0  chr11  97950000  98460000  9795  9846       +  chr11  98360000  98870000   \n",
       "1   chr2  27800000  28310000  2780  2831       +   chr2  28190000  28700000   \n",
       "2   chr8  72650000  73160000  7265  7316       +   chr8  73040000  73550000   \n",
       "3   chr7  74120000  74630000  7412  7463       +   chr7  74520000  75030000   \n",
       "4   chr9  77190000  77700000  7719  7770       +   chr9  77600000  78110000   \n",
       "\n",
       "    lo2   hi2 strand2             region  \n",
       "0  9836  9887       -  chr11:0-121843856  \n",
       "1  2819  2870       -   chr2:0-181748087  \n",
       "2  7304  7355       -   chr8:0-131738871  \n",
       "3  7452  7503       -   chr7:0-152524553  \n",
       "4  7760  7811       -   chr9:0-124076172  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snippet_flank = 250000\n",
    "\n",
    "windows1 = snipping.make_bin_aligned_windows(\n",
    "    binsize, \n",
    "    sites['chrom1'], \n",
    "    sites['mid1'],\n",
    "    flank_bp=snippet_flank)\n",
    "windows1['strand'] = sites['strand1']\n",
    "\n",
    "windows2 = snipping.make_bin_aligned_windows(\n",
    "    binsize, \n",
    "    sites['chrom2'], \n",
    "    sites['mid2'],\n",
    "    flank_bp=snippet_flank)\n",
    "windows2['strand'] = sites['strand2']\n",
    "\n",
    "windows = pd.merge(windows1, windows2, left_index=True, right_index=True, suffixes=('1', '2'))\n",
    "windows = snipping.assign_regions(windows, supports)\n",
    "windows = windows.dropna()\n",
    "windows.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:50:20.218347Z",
     "start_time": "2018-05-08T02:49:19.666969Z"
    }
   },
   "outputs": [],
   "source": [
    "stacks = {}\n",
    "piles = {}\n",
    "for cond in conditions:\n",
    "    expected = pd.read_table(f'data/{long_names[cond]}.{binsize//1000}kb.expected.cis.tsv')\n",
    "    snipper = snipping.ObsExpSnipper(clrs[cond], expected)\n",
    "    stack = snipping.pileup(windows, snipper.select, snipper.snip)\n",
    "    stacks[cond] = stack\n",
    "    piles[cond] = np.nanmean(stack, axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-05-08T02:50:21.099694Z",
     "start_time": "2018-05-08T02:50:20.220563Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7fa2abd45eb8>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa2abf44940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gs = plt.GridSpec(nrows=1, ncols=len(conditions) + 1, width_ratios=[20] * len(conditions) + [1])\n",
    "plt.figure(figsize=(6 * len(conditions), 6))\n",
    "\n",
    "opts = dict(\n",
    "    vmin=-0.5,\n",
    "    vmax=0.5,\n",
    "    extent=[-flank//1000, flank//1000, -flank//1000, flank//1000],\n",
    "    cmap='coolwarm'\n",
    ")\n",
    "\n",
    "for i, cond in enumerate(conditions):\n",
    "    ax = plt.subplot(gs[i])\n",
    "    img = ax.matshow(\n",
    "        np.log2(np.nanmean(stacks[cond], axis=2)), #piles[cond]),  \n",
    "        **opts)\n",
    "    ax.xaxis.tick_bottom()\n",
    "    if i > 0:\n",
    "        ax.yaxis.set_visible(False)\n",
    "    plt.title(long_names[cond])\n",
    "\n",
    "ax = plt.subplot(gs[len(conditions)])\n",
    "plt.colorbar(img, cax=ax)\n",
    "\n",
    "plt.suptitle(f'convergent CTCF sites ({anchor_dist//1000} +/- {anchor_flank//1000})kb apart\\n'\n",
    "             f'Hi-C resolution = {binsize//1000}kb; # of pairs = {len(windows)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": "block",
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
